Generative Artificial Intelligence (GAI), particularly text-to-image (T2I) generation tools, presents new possibilities for preserving and innovating traditional cultural patterns. However, AI-generated images often lack cultural context, which risks cultural bias and the loss of cultural significance. This study explores the use of GAI in generating culturally meaningful patterns, focusing on Chinese intangible cultural heritage Huayao cross-stitch as a case study. By applying Low-Rank Adaptation (LoRA) fine-tuning to optimize T2I tools and using in-situ interviews and focus groups, we collected feedback from 18 Huayao artisans. The results show that while fine-tuned models improved stylistic accuracy, the cultural meaning of the patterns remained insufficient. This research highlights AI's limited role in cultural innovation and emphasizes the necessity for dynamically maintaining cultural authenticity through the daily practices of cultural holders. It also reflects on how AI might have a long-term impact on the creative position of artisan communities.